Triple

T11161868
Position Surface form Disambiguated ID Type / Status
Subject Yantra River E264055 entity
Predicate flowsThrough P225 FINISHED
Object Gabrovo E343154 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Gabrovo | Statement: [Yantra River, flowsThrough, Gabrovo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gabrovo
Context triple: [Yantra River, flowsThrough, Gabrovo]
  • A. Gabrovo chosen
    Gabrovo is a town in central Bulgaria known for its humor and satire traditions, as well as its historical role in the country’s industrial development.
  • B. Targovishte
    Targovishte is a town in northeastern Bulgaria known as an administrative and economic center with historical roots dating back to the Ottoman period.
  • C. Sliven
    Sliven is a city in eastern Bulgaria known for its textile industry, historic role in Bulgarian national revival, and location near the eastern Balkan Mountains.
  • D. Asenovgrad
    Asenovgrad is a town in southern Bulgaria known as a gateway to the Rhodope Mountains and a regional center rich in historical and religious landmarks.
  • E. Blagoevgrad
    Blagoevgrad is a city in southwestern Bulgaria known as a regional cultural and educational center, home to several universities and a vibrant student population.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d6aa9ccddc8190868998c8b7beb060 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8832fe88190a74d81f9ed547baa completed April 9, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69e483747ba88190aa6ef9df2545b18b completed April 19, 2026, 7:25 a.m.
Created at: April 8, 2026, 9:29 p.m.